def model(self):
return util.merge_dicts(
dict1=super(LimitedAttributesGenerator, self).model(),
dict2=dict(provoke_collision_rate=self.provoke_collision_rate,
selected_shapes=self.selected_shapes,
selected_colors=self.selected_colors,
selected_textures=self.selected_textures))
def model(self):
return util.merge_dicts(
dict1=super(RegularTypeCaptioner, self).model(),
dict2=dict(hypernym=self.hypernym,
attributes=self.attributes,
existing_attribute=self.existing_attribute,
incorrect_mode=self.incorrect_mode))
def model(self):
return util.merge_dicts(
dict1=super(MaxAttributeCaptioner, self).model(),
dict2=dict(predtype=self.predtype,
value=self.value,
incorrect_mode=self.incorrect_mode,
scope_captioner=self.scope_captioner.model()))
def model(self):
return util.merge_dicts(
dict1=super(ComparisonRelationCaptioner, self).model(),
dict2=dict(reltype=self.reltype,
value=self.value,
incorrect_mode=self.incorrect_mode,
reference_captioner=self.reference_captioner.model()))
def model(self):
return util.merge_dicts(
dict1=super(EquivalenceCaptioner, self).model(),
dict2=dict(both_correct=self.both_correct,
first_only_correct=self.first_only_correct,
captioner1=self.captioner1.model(),
captioner2=self.captioner2.model()))
def model(self):
return util.merge_dicts(
dict1=super(AttributeTypeRelationCaptioner, self).model(),
dict2=dict(
captioner=self.captioner.model()
)
)
def model(self):
return util.merge_dicts(
dict1=super(UniqueTypeCaptioner, self).model(),
dict2=dict(
hypernym=self.hypernym,
attributes=self.attributes
)
)
def model(self):
return util.merge_dicts(
dict1=super(AbsoluteQuantifierCaptioner, self).model(),
dict2=dict(qrange=self.qrange,
quantity=self.quantity,
incorrect_mode=self.incorrect_mode,
restrictor_captioner=self.restrictor_captioner.model(),
body_captioner=self.body_captioner.model()))
def model(self):
return util.merge_dicts(
dict1=super(SingleAttributeTypeCaptioner, self).model(),
dict2=dict(
attributes=self.attributes,
existing_attribute=self.existing_attribute
)
)
def model(self):
return util.merge_dicts(
dict1=super(RegularAttributeCaptioner, self).model(),
dict2=dict(
attribute=self.attribute,
existing_attribute=self.existing_attribute
)
)
def model(self):
return util.merge_dicts(
dict1=super(NumberBoundCaptioner, self).model(),
dict2=dict(
incorrect_mode=self.incorrect_mode,
quantifier_captioner=self.quantifier_captioner.model()
)
)
def model(self):
return util.merge_dicts(
dict1=super(ConjunctionCaptioner, self).model(),
dict2=dict(
incorrect_mode=self.incorrect_mode,
captioner1=self.captioner1.model(),
captioner2=self.captioner2.model()
)
)
def model(self):
return util.merge_dicts(
dict1=super(NegationRelationCaptioner, self).model(),
dict2=dict(
negation=self.negation,
incorrect_mode=self.incorrect_mode,
relation_captioner=self.relation_captioner.model()
)
)
def model(self):
return util.merge_dicts(
dict1=super(ExistentialCaptioner, self).model(),
dict2=dict(
incorrect_mode=self.incorrect_mode,
restrictor_captioner=self.restrictor_captioner.model(),
body_captioner=self.body_captioner.model()
)
)
def model(self):
return util.merge_dicts(
dict1=super(GenericGenerator, self).model(),
dict2=dict(
num_entities=self.num_entities,
validation_space_rate=self.validation_space_rate,
test_space_rate=self.test_space_rate
)
)
def model(self):
return util.merge_dicts(
dict1=super(ComparativeQuantifierCaptioner, self).model(),
dict2=dict(qtype=self.qtype,
qrange=self.qrange,
quantity=self.quantity,
incorrect_mode=self.incorrect_mode,
restrictor_captioner=self.restrictor_captioner.model(),
comparison_captioner=self.comparison_captioner.model(),
body_captioner=self.body_captioner.model()))
def model(self):
return util.merge_dicts(dict1=super(GenericGenerator, self).model(),
dict2=dict(world_color=self.world_color,
num_entities=self.num_entities,
space_rate=self.space_rate))
def model(self):
return util.merge_dicts(dict1=super(ImplicationCaptioner,
self).model(),
dict2=dict(correct_mode=self.correct_mode,
captioner1=self.captioner1.model(),
captioner2=self.captioner2.model()))
def model(self):
return util.merge_dicts(dict1=super(CaptionerMixer, self).model(),
dict2=dict(captioner=self.captioner.model()))
def model(self):
return util.merge_dicts(
dict1=super(ReinforcedAttributesGenerator, self).model(),
dict2=dict(provoke_collision_rate=self.provoke_collision_rate))
def model(self):
return util.merge_dicts(
dict1=super(AttributesRelationCaptioner, self).model(),
dict2=dict(attribute_mode=self.attribute_mode, existing_attribute=self.existing_attribute, incorrect_mode=self.incorrect_mode)
)
